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- Juan Antonio Cuesta-Albertos, Eustasio del Barrio, Ricardo Fraiman, Carlos Matrán
- Computational Statistics & Data Analysis
- 2007

The possibility of considering random projections to identify probability distributions belonging to parametric families is explored. The results are based on considerations involving invariance… (More)

- Juan Antonio Cuesta-Albertos, Alicia Nieto-Reyes
- Computational Statistics & Data Analysis
- 2008

The computation of the Tukeydepth, also called halfspace depth, is very demanding, even in low dimensional spaces, because it requires that all possible one-dimensional projections be considered. A… (More)

- Juan Antonio Cuesta-Albertos, Mario Wschebor
- J. Complexity
- 2003

In this paper we obtain some bounds for the expectation of the logarithm of the condition number of a random matrix whose elements are independent and identically distributed random variables. We… (More)

In this paper we provide conditions under which a distribution is determined by just one randomly chosen projection. Then we apply our results to construct goodnessof-fit tests for the one and… (More)

- Juan Antonio Cuesta-Albertos, Antonio Cuevas, Ricardo Fraiman
- Statistics and Computing
- 2009

Depths are used to attempt to order the points of a multidimensional or infinite dimensional set from the “center of the set” to the “outer of it”. There are few definitions of depth which are valid… (More)

- Marina Agulló-Antolín, Juan Antonio Cuesta-Albertos, Hélène Lescornel, Jean-Michel Loubes
- J. Multivariate Analysis
- 2015

We consider a parametric deformation model for distributions. More precisely, we assume we observe J samples of random variables which are warped from an unknown distribution template. We tackle in… (More)

- Juan Antonio Cuesta-Albertos, Ricardo Fraiman
- Data Depth: Robust Multivariate Analysis…
- 2003

In this paper we extend the notion of impartial trimming to a functional data framework, and we obtain resistant estimates of the center of a functional distribution. We give mild conditions for the… (More)

Robust estimators of location and dispersion are often used in the elliptical model to obtain an uncontaminated and highly representative subsample by trimming the data outside an ellipsoid based in… (More)

In this paper we address the statistical problem of testing if a stationary process is Gaussian. The observation consists in a finite sample path of the process. Using a random projection technique… (More)